Responses to gentrification, displacement, and the loss of low end of market (LEM) rental housing in the City of Toronto: From creating to contesting displaceability
Bibliographic record
Abstract
Government efforts to respond to the current crisis in housing affordability have centred on efforts to create new supply with comparatively little attention to preservation of existing affordable, or Low End of Market (LEM), rental housing in the private market. Decades of state policies that have prioritized developer and real estate interests over tenant rights and protections have facilitated various forms of gentrification resulting in widespread erosion of affordability and losses of LEM rental housing leading to displacement of low-income tenants. \nEfforts to measure and define these losses have been challenged by a lack of data but there is evidence that they are outstripping gains in housing affordability made by government housing strategies. \nThis portfolio of work explores the loss of LEM housing and displacement in the City of Toronto including the ways in which these losses are occurring, the role of state policy in both facilitating and framing the responses to these losses, and efforts by the third sector to contest them. A key element of this exploration is the role of data in these responses. The first section of the portfolio is a review of state policy, both historical and current, and how they have shaped new forms of gentrification and displacement and what are the influences on policy preference formation in the area of housing supply. The role of data is considered in relation to understanding housing options available to the low-income renter, policy and program development and supporting advocacy for the preservation of affordable housing and efforts to contest displacement. \nThe second section mixes both quantitative and qualitative methods to review how the loss of LEM housing is being tracked in the City of Toronto and how the impact of the related displacement is being responded to and contested. A collection of datasets documenting both physical and economic losses and displacement responses are presented and analyzed accompanied by case studies of three multi-tenant housing sites of displacement involving interviews with former tenants, advocates and agency staff involved. The implications of the findings on program and policy development and community practice to preserve affordable housing and contest displacement are discussed in this section’s conclusion. \nThe final section outlines a project funded by the Canada Mortgage and Housing Corporation (CMHC) Housing Supply Challenge to develop a data solution with the capacity to monitor the iv supply and location of LEM rental housing in urban areas that could inform and support preservation-based approaches to housing supply decisions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".